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Power BI Machine Learning and OpenAI

You're reading from  Power BI Machine Learning and OpenAI

Product type Book
Published in May 2023
Publisher Packt
ISBN-13 9781837636150
Pages 308 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Greg Beaumont Greg Beaumont
Profile icon Greg Beaumont

Table of Contents (21) Chapters

Preface Part 1: Data Exploration and Preparation
Chapter 1: Requirements, Data Modeling, and Planning Chapter 2: Preparing and Ingesting Data with Power Query Chapter 3: Exploring Data Using Power BI and Creating a Semantic Model Chapter 4: Model Data for Machine Learning in Power BI Part 2: Artificial Intelligence and Machine Learning Visuals and Publishing to the Power BI Service
Chapter 5: Discovering Features Using Analytics and AI Visuals Chapter 6: Discovering New Features Using R and Python Visuals Chapter 7: Deploying Data Ingestion and Transformation Components to the Power BI Cloud Service Part 3: Machine Learning in Power BI
Chapter 8: Building Machine Learning Models with Power BI Chapter 9: Evaluating Trained and Tested ML Models Chapter 10: Iterating Power BI ML models Chapter 11: Applying Power BI ML Models Part 4: Integrating OpenAI with Power BI
Chapter 12: Use Cases for OpenAI Chapter 13: Using OpenAI and Azure OpenAI in Power BI Dataflows Chapter 14: Project Review and Looking Forward Index Other Books You May Enjoy

Summary

In this chapter, you added R and Python visuals to your Power BI reports to discover new features in the FAA Wildlife Strike data. Using an R correlation plot, you were able to interactively slice and dice several incident flag values for positive and negative correlations. With Python histograms you took a look at the impact of speed and height on the outcomes for your planned Power BI ML models. Finally, you added new features to your Predict Damage, Predict Size, and Predict Height ML queries that will be used for ML in Power BI.

In the next chapter, you will begin migrating content to the Power BI cloud service. After migrating the Power BI dataset and report, you will then migrate the Power Query scripts to dataflows for use with Power BI ML.

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